Door lock control data processing method and device, program product, medium and door lock

Abstract

The invention discloses a door lock control data processing method and device, a program product, a medium and a door lock, the door lock is provided with a touch screen, and the method comprises the steps that a current character written by a current user on the touch screen is acquired; acquiring historical characters stored in history, wherein the historical characters comprise characters written by a legal user; determining the similarity between the current character and the historical character; if the similarity is larger than or equal to a first similarity threshold value, a control signal for opening the door lock is triggered. Through the technical scheme provided by the invention, the convenience of using the door lock by the user can be improved.

Description

Technical Field

[0001] This application belongs to the field of intelligent door lock control technology, and in particular relates to a door lock control data processing method, program product, device, medium and door lock. Background Technology

[0002] Currently, smart locks, such as combination locks, are gradually gaining popularity among consumers. However, due to the small screen size and densely packed numeric characters, manually entering the password increases the difficulty. This is mainly manifested in users accidentally pressing other numbers when unlocking, affecting the success rate of password unlocking. This is especially challenging for people with poor eyesight (such as cataract patients), and their convenience needs to be improved. Therefore, how to improve the convenience of using locks and enhance the user experience is an urgent technical problem to be solved. Summary of the Invention

[0003] The embodiments of this application provide a door lock control data processing method, device, program product, medium, and door lock, which can at least to some extent improve the convenience of users using door locks.

[0004] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0005] According to a first aspect of the embodiments of this application, a door lock control data processing method is provided, wherein the door lock is configured with a touch screen, the method comprising: acquiring a current character written by a current user on the touch screen; acquiring historical characters saved in the past, the historical characters including characters written by legitimate users; determining the similarity between the current character and the historical characters; and triggering a control signal to open the door lock if the similarity is greater than or equal to a first similarity threshold.

[0006] In some embodiments of this application, based on the foregoing scheme, determining the similarity between the current character and the historical character includes: extracting the current handwriting features of the current character and the historical handwriting features of the historical character, and determining the similarity between the current character and the historical character based on the current handwriting features and the historical handwriting features; or extracting the current character content of the current character and the historical character content of the historical character, and determining the similarity between the current character and the historical character based on the current character content and the historical character content; or extracting the current handwriting features and current character content of the current character, the historical handwriting features and historical character content of the historical character, and determining the similarity between the current character and the historical character based on the current handwriting features and the current character content, the historical handwriting features and the historical character content.

[0007] In some embodiments of this application, based on the foregoing scheme, determining the similarity between the current character and the historical character further includes: obtaining a first writing habit feature of the current user during the process of writing the current character, and obtaining a second writing habit feature of a legitimate user during the process of writing the historical character, wherein the writing habit feature includes at least one of writing speed, writing acceleration, writing force, and stroke order; and determining the similarity between the current character and the historical character based on the first writing habit feature and the second writing habit feature.

[0008] In some embodiments of this application, based on the foregoing scheme, determining the similarity between the current character and the historical character includes: training a first machine learning model based on the historical character, so that the first machine learning model learns the character content and / or handwriting features of the historical character; and determining the similarity between the current character and the historical character through the first machine learning model.

[0009] In some embodiments of this application, based on the foregoing scheme, the method further includes: if the similarity is greater than or equal to a first similarity threshold, saving the current character as the historical character.

[0010] In some embodiments of this application, based on the foregoing scheme, the method further includes: obtaining characters written by a legitimate user; training a second machine learning model based on the characters written by the legitimate user, so that the second machine learning model learns the handwriting features and / or character content of the characters written by the legitimate user; deriving new characters through the second machine learning model, and saving the new characters as the historical characters.

[0011] In some embodiments of this application, based on the foregoing scheme, the method further includes: encrypting the historical characters using an encryption algorithm before saving the historical characters.

[0012] In some embodiments of this application, based on the foregoing scheme, the method further includes: if the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold, triggering a prompt signal to rewrite characters; if the number of times the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold is detected is greater than or equal to a preset number, triggering an alarm signal; if the similarity is less than the second similarity threshold, triggering an alarm signal.

[0013] According to a second aspect of the embodiments of this application, a door lock control data processing device is provided. The door lock is equipped with a touch screen. The device includes: a first acquisition unit, configured to acquire a current character written by a current user on the touch screen; a second acquisition unit, configured to acquire historical characters saved in history, the historical characters including characters written by legitimate users; a determination unit, configured to determine the similarity between the current character and the historical characters; and a triggering unit, configured to trigger a control signal to open the door lock if the similarity is greater than or equal to a first similarity threshold.

[0014] According to a third aspect of the embodiments of this application, a computer program product is provided, the computer program product including computer instructions stored in a computer-readable storage medium and adapted to be read and executed by a processor to cause a computer device having the processor to perform an operation as described in any of the first aspects above.

[0015] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing at least one computer program instruction, the at least one computer program instruction being loaded and executed by a processor to perform the operation as described in any of the first aspects above.

[0016] According to a fifth aspect of the present application, a door lock is provided, the door lock including one or more processors and one or more memories, the one or more memories storing at least one computer program instruction, the at least one computer program instruction being loaded and executed by the one or more processors to implement the method described in any of the embodiments of the first aspect above.

[0017] Based on the technical solution proposed in this application, the similarity between the current character written by the current user on the touchscreen and the historical characters saved by a legitimate user is first determined. If the similarity is greater than or equal to a preset first similarity threshold, it can be concluded that the current user's character writing is considered legitimate, thereby triggering the control signal to open the door lock. This effectively solves the problem of accidental touches caused by the small screen size and narrow character spacing in existing technologies, thus improving the convenience of using the door lock and enhancing the user experience. At the same time, the technical solution proposed in this application also avoids the problem of inconsistent traces at certain numbers on the door lock screen due to frequent pressing, which could make the password easily cracked, thereby improving the security of door lock use and control.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0020] Figure 1 A schematic diagram of a door lock from an embodiment of this application is shown;

[0021] Figure 2 A system architecture diagram showing the technical solutions applicable to embodiments of this application is illustrated.

[0022] Figure 3 A flowchart of the door lock control data processing method in an embodiment of this application is shown;

[0023] Figure 4 A block diagram of a door lock control data processing device according to an embodiment of this application is shown;

[0024] Figure 5 A schematic diagram of the door lock structure in an embodiment of this application is shown. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0027] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0028] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0029] It should be noted that "multiple" in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0030] It should also be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such uses of these terms can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described.

[0031] To enable those skilled in the art to better understand this application, firstly, in conjunction with Figure 1 A brief description of the door locks involved in this application is provided.

[0032] See Figure 1 The diagram shows a door lock in an embodiment of this application.

[0033] like Figure 1 As shown in neutron graph (a), the door lock 100 described in this application includes a touch screen 101. The touch screen 101 can be used by a user to write characters (i.e., text or symbols). Specifically, the user can use a finger or a light pen to slide along a certain trajectory on the touch screen 101 to write characters. In one embodiment of practical application, when the user approaches the door lock or touches the door lock with their hand, the touch screen 101 can switch from a black screen state to a bright screen state to facilitate the user writing characters on the touch screen. Specifically, as shown in the figure... Figure 1 In region 102 shown in neutron diagram (b), the user can write text on the touchscreen 101, such as... Figure 1 In the area 103 shown in neutron diagram (c), the user can also write certain graphic symbols on the touch screen 101.

[0034] In this application, by obtaining the characters written by the user, it is possible to verify whether the user is a legitimate user, and thus determine whether to unlock the door for the user.

[0035] Figure 2A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown.

[0036] like Figure 2 As shown, the system architecture may include a door lock 100, a network 201, and a server 202. The network 201 serves as the medium for providing a communication link between the door lock 100 and the server 202. The network 201 may include various connection types, such as wired communication links, wireless communication links, etc.

[0037] It should also be noted that, Figure 2 The number of door locks, networks, and servers shown is merely illustrative. Depending on the implementation requirements, the servers can be independent physical servers, server clusters or distributed systems composed of multiple physical servers, or cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0038] It should be noted that the door lock control data processing method provided in this application embodiment can be executed by the server 202. Accordingly, the door lock control data processing device is generally set in the server 202.

[0039] It should also be noted that the door lock control data processing method provided in this application embodiment can also be executed by the door lock 100. The main control board of the door lock 100 can be configured with an AI computing chip, which can process information calculations at the level of millions, thereby laying the hardware foundation for executing the technical solution proposed in this application.

[0040] Next, this application will elaborate on the proposed door lock control data processing scheme.

[0041] Reference Figure 3 The flowchart of a door lock control data processing method according to an embodiment of this application is shown. The door lock is equipped with a touchscreen, and the door lock control data processing method can be executed by a device with computing capabilities. (Refer to...) Figure 3 As shown, the door lock control data processing method includes at least steps 310 to 340, which are described in detail below:

[0042] Step 310: Obtain the current character written by the current user on the touch screen.

[0043] Step 320: Obtain historical characters saved in history, including characters written by legitimate users.

[0044] Step 330: Determine the similarity between the current character and the historical character.

[0045] Step 340: If the similarity is greater than or equal to the first similarity threshold, then trigger the control signal to open the door lock.

[0046] In this application, for example, such as Figure 2 The door lock 100 or server 202 shown can obtain the current character handwritten by the current user on the touch screen, and further obtain historically saved characters. These historical characters may include characters previously written and saved by legitimate users. Then, using character recognition algorithms or artificial intelligence technology, the current character and the historical characters can be compared to assess their similarity. If the similarity between the current character and the historical character is greater than or equal to a preset first similarity threshold (e.g., 80%, or 85%, this application does not specifically limit the first similarity threshold), it can be said to some extent that the current user's character writing is considered legitimate, that is, the current user can be determined to be a legitimate user. In this case, a control signal to open the door lock can be triggered, thereby allowing the door lock to open.

[0047] Based on the technical solution proposed in this application, the problem of accidental touches caused by the small screen size and small character spacing of smart locks in existing technologies is effectively solved, thereby improving the convenience of using the lock and enhancing the user experience. At the same time, the technical solution proposed in this application can also avoid the problem that frequent pressing of certain numbers on the lock screen can cause inconsistent marks, making it easy for unauthorized individuals to crack the password, thus improving the security of the lock.

[0048] In such Figure 3 In step 330, determining the similarity between the current character and the historical character can be performed according to any one of the following steps 331 to 333:

[0049] Step 331: Extract the current handwriting features of the current character and the historical handwriting features of the historical character, and determine the similarity between the current character and the historical character based on the current handwriting features and the historical handwriting features.

[0050] In this application, it should be noted that handwriting features may include at least one of the following dimensions: stroke features, character shape features, character spacing features, and writing style features.

[0051] Among them, stroke characteristics can include the thickness of the strokes (different stroke thicknesses can reflect the writing tool and writing pressure), the continuity of the strokes (whether the connection between strokes is smooth and whether there are breaks), and the beginning and ending of the strokes (the way of starting and ending the strokes can show the writer's personality); character shape characteristics can include the size of the character (the overall size and relative size of the character), the shape of the character (the overall outline and structure of the character, such as square, round, etc.), and the slant of the character (whether the character is upright or slanted, and at what angle); character spacing characteristics can include character spacing (whether the distance between characters is uniform), and line spacing (the distance between lines, whether it appears crowded or sparse); writing style characteristics can include different writing styles such as regular script, running script, and cursive script, or the unique habits of an individual when writing, such as specific stroke treatment or character shape deformation.

[0052] In this application, the similarity between the current character and the historical character is determined by the current handwriting features and the historical handwriting features. This allows for the determination of whether the current character matches a previously saved historical character, thereby improving the accuracy and reliability of character similarity recognition and ultimately enhancing the security of door lock use and control.

[0053] Step 332: Extract the current character content of the current character and the historical character content of the historical character, and determine the similarity between the current character and the historical character based on the current character content and the historical character content.

[0054] In this application, for example, the character content can be a string of numbers, a string of Chinese characters, a string of foreign characters, or a combination of multiple characters including numbers, Chinese characters, and foreign characters. Furthermore, the character content can also be a graphic symbol. By determining the similarity between the current character and the historical character content, it is possible to judge whether the current character matches a previously saved historical character, thereby improving the accuracy and reliability of character similarity recognition, and ultimately enhancing the security of door lock use and control.

[0055] Step 333: Extract the current handwriting features and current character content of the current character, the historical handwriting features and historical character content of the historical characters, and determine the similarity between the current character and the historical characters based on the current handwriting features and current character content, the historical handwriting features and historical character content.

[0056] In this application, when determining the similarity between the current character and the historical character, both the handwriting features and the character content are considered simultaneously. The advantage of this approach is that:

[0057] First, it enables multi-dimensional analysis of characters. Relying solely on handwriting features or character content to determine similarity can lead to misjudgments. For example, different users may write similar characters, while the same user's handwriting at different times may show slight differences. By comprehensively analyzing both handwriting features and character content, a more complete picture of a user's writing habits and characteristics can be captured, thereby improving recognition accuracy.

[0058] Secondly, it can effectively prevent deceptive attempts to unlock doors by merely imitating handwriting or stealing character content. For example, even if an unauthorized user imitates the handwriting of a legitimate user, if the character content does not match, the current character cannot achieve a high degree of similarity with historical characters. Similarly, even if an unauthorized user steals character content from a legitimate user, if the handwriting features do not match, the current character cannot achieve a high degree of similarity with historical characters.

[0059] Furthermore, by comprehensively considering both handwriting characteristics and character content, we can be more tolerant of minor variations in a user's handwriting. For example, a user's handwriting may differ at different times or in different environments, but matching the character content can provide additional verification evidence, reduce false positives, and improve robustness.

[0060] Finally, combining handwriting features and character content can effectively reduce errors caused by single feature analysis. Handwriting features may be affected by factors such as user emotions and writing speed, while character content is relatively stable. Combining the two can complement each other, reduce errors, improve the overall accuracy of similarity judgment, and thus enhance the security of door lock use and control.

[0061] As can be seen, based on the technical solution in step 333 above, considering both handwriting features and character content, a more comprehensive and accurate analysis can be provided, thereby significantly improving the accuracy of similarity judgment and enhancing the security and reliability of door lock control.

[0062] In such Figure 3 In step 330, determining the similarity between the current character and the historical character can also be performed according to steps 334 to 335 as follows:

[0063] Step 334: Obtain the first writing habit feature of the current user in the process of writing the current character, and obtain the second writing habit feature of the legitimate user in the process of writing the historical character, wherein the writing habit feature includes at least one of writing speed, writing acceleration, writing force and stroke order;

[0064] Step 335: Determine the similarity between the current character and the historical character based on the first writing habit feature and the second writing habit feature.

[0065] In this application, by acquiring the first writing habit features of the current user during the character writing process and the second writing habit features of the legitimate user during the historical character writing process, the accuracy of character similarity judgment can be significantly improved. The writing habit features include at least one of the following: writing speed (i.e., the speed at which the finger or stylus slides on the touchscreen during writing), writing acceleration (i.e., the degree of change in the speed at which the finger or stylus slides on the touchscreen during writing), writing pressure (i.e., the pressure applied to the touchscreen by the finger or stylus during writing), and stroke order. These features can comprehensively reflect the user's writing behavior.

[0066] By analyzing these dynamic features, more subtle differences in writing habits can be captured, reducing misjudgments caused by static handwriting similarity. Furthermore, features such as writing speed, writing acceleration, and writing pressure are difficult to imitate, thus enhancing the security and reliability of user authentication and effectively preventing forgery and deception. Stroke order, as an important indicator of writing habits, further improves recognition accuracy. Combining these writing habit features allows for a more accurate determination of the similarity between the current character and historical characters, thereby improving the reliability and robustness of overall similarity recognition and ultimately enhancing the security of door lock use and control.

[0067] In such Figure 3 In step 330 shown, determining the similarity between the current character and the historical character can also be performed according to steps 336 to 337 as follows:

[0068] Step 336: Train the first machine learning model based on the historical characters so that the first machine learning model learns the character content and / or handwriting features of the historical characters.

[0069] Step 337: Determine the similarity between the current character and the historical character using the first machine learning model.

[0070] In this application, by training a first machine learning model based on historical characters, the model can learn and understand the content and / or handwriting features of historical characters written by legitimate users, thereby significantly improving the accuracy and reliability of character similarity judgment. In particular, it enables the first machine learning model to recognize and distinguish different handwriting styles. Even if the user writes characters different from historical characters, the model can determine the similarity between the current character and historical characters by analyzing handwriting features, enhancing the adaptability of character similarity recognition in different situations. This overall improves the intelligence and reliability of character similarity recognition, thereby enhancing the security of door lock use and control.

[0071] In this application, the following step 351 may also be performed:

[0072] Step 351: If the similarity is greater than or equal to the first similarity threshold, the current character is saved as the historical character.

[0073] In this application, when the similarity of the characters written by the user is greater than or equal to a first similarity threshold, it indicates that the current user is a legitimate user. At this point, the characters written by the legitimate user are saved as historical characters, allowing for real-time dynamic capture of character data during each identification process, enriching the historical character data used to verify user identity. As the number of times a user uses the service increases, the accuracy and efficiency of user authentication will gradually improve, making it increasingly user-friendly.

[0074] In this application, steps 352 to 354 may also be performed:

[0075] Step 352: Obtain the characters written by the legitimate user.

[0076] Step 353: Train the second machine learning model based on the characters written by the legitimate user, so that the second machine learning model learns the handwriting features and / or character content of the characters written by the legitimate user.

[0077] Step 354: Derive new characters using the second machine learning model and save the new characters as historical characters.

[0078] In this application, authorized users can write characters into an app or the door lock touchscreen. Based on this character data, a second machine learning model is trained to learn and recognize the user's handwriting features and / or character content. Through this training, the second machine learning model effectively masters the user's personalized writing style and the content of specific characters. After the second machine learning model is trained, new characters are derived from it and saved as historical characters. In this way, the character database of authorized users can be continuously enriched and improved, thereby enhancing overall recognition performance and user experience. Ultimately, with continuous use and training accumulation of characters, the accuracy and efficiency of character recognition will significantly improve, making door lock unlocking control increasingly intelligent and user-friendly.

[0079] In this application, the following step 350 may also be performed:

[0080] Step 350: Before saving the historical characters, the historical characters are encrypted using an encryption algorithm.

[0081] In this application, the historical characters are encrypted using an encryption algorithm before being saved. This prevents the illegal acquisition and tampering of legitimate users' character data, reduces the risk of misuse of legitimate users' character data, protects user identity privacy, and ensures the security of character data.

[0082] In this application, steps 361 to 362 may also be performed:

[0083] Step 361: If the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold, a prompt signal for rewriting characters is triggered; if the number of times the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold is detected is greater than or equal to a preset number, an alarm signal is triggered.

[0084] Step 362: If the similarity is less than the second similarity threshold, an alarm signal is triggered.

[0085] In this application, when the similarity is less than the first similarity threshold but greater than or equal to the second similarity threshold (e.g., 60%, or 65%, though this application does not specifically limit the second similarity threshold), it may be due to user error during character input. In this case, the door lock can be triggered to issue a prompt signal, prompting the user to rewrite the character. This avoids the problem of the door lock being unable to open due to user error, improving the door lock's security and user experience. If the door lock repeatedly detects similarity within the above range, and the number of times reaches or exceeds a preset threshold, an alarm signal can be triggered, indicating possible abnormal operation, further enhancing security. When the similarity is lower than the second similarity threshold, the system can immediately trigger an alarm signal, indicating that the similarity between the currently input character and historical characters is too low, potentially indicating a risk of illegal operation. Through these multi-layered detection and response mechanisms, the door lock can not only effectively identify legitimate user input but also issue timely alarms in abnormal situations to prevent unauthorized access, ensuring the door lock's security and reliability.

[0086] The following describes an embodiment of the apparatus described in this application, which can be used to execute the door lock control data processing method described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the door lock control data processing method described above in this application.

[0087] See Figure 4 The diagram shows a block diagram of a door lock control data processing device according to an embodiment of this application, wherein the door lock is equipped with a touch screen.

[0088] like Figure 4As shown, the door lock control data processing device 400 according to an embodiment of this application includes: a first acquisition unit 401, a second acquisition unit 402, a determination unit 403, and a triggering unit 404.

[0089] The system includes a first acquisition unit 401 for acquiring the current character written by the current user on the touch screen; a second acquisition unit 402 for acquiring historical characters saved in the past, including characters written by legitimate users; a determination unit 403 for determining the similarity between the current character and the historical character; and a trigger unit 404 for triggering a control signal to open the door lock if the similarity is greater than or equal to a first similarity threshold.

[0090] In some embodiments of this application, based on the foregoing scheme, the triggering unit 404 is configured to: trigger a prompt signal for rewriting characters if the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold; trigger an alarm signal if the number of times the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold is greater than or equal to a preset number; and trigger an alarm signal if the similarity is less than the second similarity threshold.

[0091] In some embodiments of this application, based on the foregoing scheme, the device further includes: a storage unit, used to save the current character as the historical character if the similarity is greater than or equal to a first similarity threshold.

[0092] In some embodiments of this application, based on the foregoing scheme, the storage unit is configured to: acquire characters written by a legitimate user; train a second machine learning model based on the characters written by the legitimate user, so that the second machine learning model learns the handwriting features and / or character content of the characters written by the legitimate user; derive new characters through the second machine learning model, and save the new characters as the historical characters.

[0093] In some embodiments of this application, based on the foregoing scheme, the storage unit is configured to encrypt the historical characters using an encryption algorithm before saving them.

[0094] In some embodiments of this application, based on the foregoing scheme, the determining unit 403 is configured to: extract the current handwriting features of the current character and the historical handwriting features of the historical character, and determine the similarity between the current character and the historical character based on the current handwriting features and the historical handwriting features; or extract the current character content of the current character and the historical character content of the historical character, and determine the similarity between the current character and the historical character based on the current character content and the historical character content; or extract the current handwriting features and current character content of the current character, the historical handwriting features and historical character content of the historical character, and determine the similarity between the current character and the historical character based on the current handwriting features and the current character content, the historical handwriting features and the historical character content.

[0095] In some embodiments of this application, based on the foregoing scheme, the determining unit 403 is configured to: obtain a first writing habit feature of the current user during the process of writing the current character, and obtain a second writing habit feature of the legitimate user during the process of writing the historical character, wherein the writing habit feature includes at least one of writing speed, writing acceleration, writing force, and stroke order; and determine the similarity between the current character and the historical character based on the first writing habit feature and the second writing habit feature.

[0096] In some embodiments of this application, based on the foregoing scheme, the determining unit 403 is configured to: train a first machine learning model based on the historical characters, so that the first machine learning model learns the character content and / or handwriting features of the historical characters; and determine the similarity between the current character and the historical characters through the first machine learning model.

[0097] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium storing at least one computer program instruction, which is loaded and executed by a processor to perform the operations described above.

[0098] Based on the same inventive concept, embodiments of this application provide a computer program product, the computer program product including computer instructions stored in a computer-readable storage medium and adapted to be read and executed by a processor to cause a computer device having the processor to perform the operations performed as described above.

[0099] Based on the same inventive concept, this application also provides a door lock, see reference. Figure 5The diagram shows a schematic of the structure of a door lock in an embodiment of this application. The door lock includes one or more memories 504, one or more processors 502, and at least one computer program (computer program instructions) stored in the memory 504 and executable on the processor 502. When the processor 502 executes the computer program, it implements the method described above.

[0100] Among them, Figure 5 In this document, a bus architecture (represented by bus 500) is used. Bus 500 may include any number of interconnected buses and bridges, linking various circuits including one or more processors represented by processor 502 and memory represented by memory 504. Bus 500 may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 505 provides an interface between bus 500 and receiver 501 and transmitter 503. Receiver 501 and transmitter 503 may be the same element, i.e., a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 502 is responsible for managing bus 500 and general processing, while memory 504 can be used to store data used by processor 502 during operation.

[0101] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this application and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0102] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0103] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0104] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing computer program instructions, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0105] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A door lock control data processing method, characterized in that, The door lock is equipped with a touch screen, and the method includes: Get the current character written by the current user on the touch screen; Retrieve historical characters saved in the past, including characters written by legitimate users; Determine the similarity between the current character and the historical characters; If the similarity is greater than or equal to the first similarity threshold, a control signal to open the door lock is triggered.

2. The method according to claim 1, characterized in that, Determining the similarity between the current character and the historical characters includes: Extract the current handwriting features of the current character and the historical handwriting features of the historical characters, and determine the similarity between the current character and the historical characters based on the current handwriting features and the historical handwriting features; or Extract the current character content of the current character and the historical character content of the historical characters, and determine the similarity between the current character and the historical characters based on the current character content and the historical character content; or Extract the current handwriting features and current character content of the current character, the historical handwriting features and historical character content of the historical characters, and determine the similarity between the current character and the historical characters based on the current handwriting features and current character content, the historical handwriting features and historical character content.

3. The method according to claim 2, characterized in that, Determining the similarity between the current character and the historical characters further includes: The system obtains a first writing habit feature of the current user during the process of writing the current character, and a second writing habit feature of a legitimate user during the process of writing the historical character. The writing habit feature includes at least one of writing speed, writing acceleration, writing force, and stroke order. Based on the first writing habit feature and the second writing habit feature, the similarity between the current character and the historical character is determined.

4. The method according to claim 1, characterized in that, Determining the similarity between the current character and the historical characters includes: The first machine learning model is trained based on the historical characters so that the first machine learning model learns the character content and / or handwriting features of the historical characters. The similarity between the current character and the historical characters is determined by the first machine learning model.

5. The method according to claim 1, characterized in that, The method further includes: If the similarity is greater than or equal to the first similarity threshold, the current character is saved as the historical character.

6. The method according to claim 1, characterized in that, The method further includes: Retrieve characters written by a legitimate user; The second machine learning model is trained based on the characters written by the legitimate user, so that the second machine learning model learns the handwriting features and / or character content of the characters written by the legitimate user. New characters are derived through the second machine learning model, and these new characters are saved as historical characters.

7. The method according to claim 5 or 6, characterized in that, The method further includes: Before saving the historical characters, the historical characters are encrypted using an encryption algorithm.

8. The method according to claim 1, characterized in that, The method further includes: If the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold, a prompt signal for rewriting characters is triggered; if the number of times the similarity is less than the first similarity threshold and greater than or equal to the second similarity threshold is detected is greater than or equal to a preset number, an alarm signal is triggered. If the similarity is less than the second similarity threshold, an alarm signal is triggered.

9. A door lock control data processing device, characterized in that, The door lock is equipped with a touch screen, and the device includes: The first acquisition unit is used to acquire the current character written by the current user on the touch screen; The second acquisition unit is used to acquire historical characters saved in history, including characters written by legitimate users; A determining unit is used to determine the similarity between the current character and the historical character; A triggering unit is used to trigger a control signal to open the door lock if the similarity is greater than or equal to a first similarity threshold.

10. A computer program product, characterized in that, The computer program product includes computer instructions stored in a computer-readable storage medium and adapted to be read and executed by a processor to cause a computer device having the processor to perform the method as claimed in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to perform the operations performed by the method as described in any one of claims 1 to 8.

12. A door lock, characterized in that, The door lock includes one or more processors and one or more memories, wherein the one or more memories store at least one piece of program code, which is loaded and executed by the one or more processors to implement the method as claimed in any one of claims 1 to 8.

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